Types of compute instances
SageMaker geospatial capabilities offer three types of compute instances.
-
SageMaker Studio Classic geospatial notebook instances – SageMaker geospatial supports both CPU and GPU-based notebook instances in Studio Classic. Notebook instances are used to build, train, and deploy ML models. For a list of available notebook instance types that work with the geospatial image, see Supported notebook instance types.
-
SageMaker geospatial jobs instances – Run processing jobs to transform satellite image data.
-
SageMaker geospatial model inference types – Make predictions by using pre-trained ML models on satellite imagery.
The instance type is determined by the operations that you run.
The following table shows the available SageMaker geospatial specific operations and instance types that you can use.
|
Operations |
Instance |
|---|---|
Temporal Statistics |
ml.geospatial.jobs |
Zonal Statistics |
ml.geospatial.jobs |
Resampling |
ml.geospatial.jobs |
Geomosaic |
ml.geospatial.jobs |
Band Stacking |
ml.geospatial.jobs |
Band Math |
ml.geospatial.jobs |
Cloud Removal with Landsat8 |
ml.geospatial.jobs |
Cloud Removal with Sentinel-2 |
ml.geospatial.models |
Cloud Masking |
ml.geospatial.models |
Land Cover Segmentation |
ml.geospatial.models |
SageMaker geospatial supported notebook instance types
SageMaker geospatial supports both CPU and GPU-based notebook instances in Studio Classic. If when starting a
GPU enabled notebook instance you receive a ResourceLimitExceeded
error, you need to request a quota increase. To get started on a Service Quotas quota
increase request, see Requesting a quota
increase in the Service Quotas User Guide.
Supported Studio Classic notebook instance types
|
Name |
Instance type |
|---|---|
ml.geospatial.interactive |
CPU |
ml.g5.xlarge |
GPU |
ml.g5.2xlarge |
GPU |
ml.g5.4xlarge |
GPU |
ml.g5.8xlarge |
GPU |
ml.g5.16xlarge |
GPU |
ml.g5.12xlarge |
GPU |
ml.g5.24xlarge |
GPU |
ml.g5.48xlarge |
GPU |
You are charged different rates for each type of compute instance that you use. For more
information about pricing, see Geospatial ML with Amazon SageMaker
SageMaker geospatial libraries
The SageMaker geospatial specific Instance type,
ml.geospatial.interactive contains the following Python
libraries.
Geospatial libraries available on the geospatial instance type
|
Library name |
Version available |
|---|---|
| numpy | 1.23.4 |
| scipy | 1.11.2 |
| pandas | 1.4.4 |
| gdal | 3.2.2 |
| fiona | 1.8.22 |
| geopandas | 0.11.1 |
| shapely | 1.8.4 |
| seaborn | 0.11.2 |
| notebook | 1.8.22 |
| scikit-image | 0.11.2 |
| rasterio | 6.4.12 |
| scikit-learn | 0.19.2 |
| ipyleaflet | 1.0.1 |
| rtree | 0.17.2 |
| opencv | 4.6.0.66 |
| supy | 2022.4.7 |
| SNAP toolbox | 9.0 |
| cdsapi | 0.6.1 |
| arosics | 1.8.1 |
| rasterstats | 0.18.0 |
| rioxarray | 0.14.1 |
| pyroSAR | 0.20.0 |
| eo-learn | 1.4.1 |
| deepforest | 1.2.7 |
| scrapy | 2.8.0 |
| netCDF4 | 1.6.3 |
| xarray[complete] | 0.20.1 |
| Orfeotoolbox | OTB-8.1.1 |
| pytorch | 2.0.1 |
| pytorch-cuda | 11.8 |
| torchvision | 0.15.2 |
| torchaudio | 2.0.2 |
| pytorch-lightning | 2.0.6 |
| tensorflow | 2.13.0 |
